Wang, Lijuan, Yan, Yong, Reda, Kamel (2018) Enhancing the performance of a rotational speed measurement system through data fusion. In: Journal of Physics: Conference Series. 1065. pp. 1-4. IOP Publishing (doi:10.1088/1742-6596/1065/7/072024) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:77849)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication) | |
Official URL: http://dx.doi.org/10.1088/1742-6596/1065/7/072024 |
Abstract
Electrostatic sensors with a single electrode or double electrodes have been applied for rotational speed measurement. In order to improve the performance of the rotational speed measurement system based on double electrostatic sensors, a data fusion algorithm is incorporated in the system. Two independent signals are accessible from the electrostatic sensor with double electrodes. From these signals two independent rotational speed measurements are obtained through auto-correlation processing of each signal and the third rotational speed measurement is also achieved by cross-correlating the two signals. A data fusion algorithm is then applied to optimally combine the three measurements. The system with the data fusion algorithm is capable of producing more accurate and more robust measurements than previous double-sensor system with a wider measurement range. Experimental results suggest that the relative error of the improved system is mostly within ±0.5% over the speed range of 200 rpm - 3000 rpm.
Item Type: | Conference or workshop item (Proceeding) |
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DOI/Identification number: | 10.1088/1742-6596/1065/7/072024 |
Uncontrolled keywords: | Rotational speed measurement |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA165 Engineering instruments, meters etc. Industrial instrumentation |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Lijuan Wang |
Date Deposited: | 25 Oct 2019 16:34 UTC |
Last Modified: | 05 Nov 2024 12:42 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/77849 (The current URI for this page, for reference purposes) |
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